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undergraduate thesis
Usporedba modela strojnog učenja za problem regresije
2023. urn:nbn:hr:190:616332
Medur, Patrik
University of Rijeka
Faculty of Engineering
Department of Computer Engineering

Cite this document

Medur, P. (2023). Usporedba modela strojnog učenja za problem regresije (Undergraduate thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:616332

Medur, Patrik. "Usporedba modela strojnog učenja za problem regresije." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:616332

Medur, Patrik. "Usporedba modela strojnog učenja za problem regresije." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:616332

Medur, P. (2023). 'Usporedba modela strojnog učenja za problem regresije', Undergraduate thesis, University of Rijeka, Faculty of Engineering, accessed 21 December 2024, https://urn.nsk.hr/urn:nbn:hr:190:616332

Medur P. Usporedba modela strojnog učenja za problem regresije [Undergraduate thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2023 [cited 2024 December 21] Available at: https://urn.nsk.hr/urn:nbn:hr:190:616332

P. Medur, "Usporedba modela strojnog učenja za problem regresije", Undergraduate thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:190:616332

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Metadata
TitleUsporedba modela strojnog učenja za problem regresije
Title (english)Comparison of machine learning models for a regression problem
AuthorPatrik Medur
MentorGoran Mauša (mentor)
Committee memberMiroslav Joler (predsjednik povjerenstva)
Committee memberGoran Mauša (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
(Department of Computer Engineering)
Rijeka
Defense date and country2023-07-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Artificial Intelligence
Abstract
U ovom radu bit će objašnjeni koncepti strojnog učenja i njegove primjene nad skupovima podataka iz UCI repozitorija. Opisat će se tehnologije korištene za izradu modela strojnog ućenja i korišteni koncepti za prikaz točnosti i učinkovitosti istreniranih modela. Prikazat će se skupovi podataka koji su bili korišteni za treniranje modela kao i tehnike s kojima su skupovi podataka predobrađeni. Istrenirani modeli će biti međusobno uspoređeni, te rangirani prema ocjenama točnosti i učinkovitosti. Na kraju objasnit će se nedostaci dobivenih modela i predložit poboljšanja za buduće modele.
Abstract (english)
This paper will explain concepts of machine learning and its application on datasets from the UCI repository. Technologies used to create machine learning models and concepts used to demonstrate the accuracy and efficiency of trained models will be described. Datasets that were used to train the models as well as the techniques with which the data sets were pre-processed will be overviewed. Trained models will be compared with each other and ranked according to accuracy and efficiency ratings. Lastly shortcomings of the obtained models will be explained and improvements will be suggested for future models.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:616332
Study programmeTitle: Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence Attribution 4.0 International (CC BY 4.0) icon
Created on2023-07-13 15:59:42